1. Field of the Invention
The present invention relates to a stereo matching system and a stereo matching method using the same.
2. Description of the Related Art
In general, stereo matching refers to estimating disparity as a distance between corresponding points of two images that are obtained by different view points using distance perception ability in a human visual system, and to obtaining a precise and reliable disparity map.
In addition, the disparity map is implemented as a depth map to recover a three-dimensional image for providing depth perception.
Stereo matching may be used in various fields, such as information communication, broadcasting, medicine, games, displays, and so on, which may be referred to as core technology of three-dimensional multimedia.
Stereo matching generally uses a local method. The local method sets a certain block region around a reference pixel of a left image as a reference image among input left and right images.
Then, the stereo matching method finds a region in the right image most closely corresponding to the certain block region around the reference pixel of the left image, to thereby estimate disparity and obtain the disparity map.
The local method includes a Sum of Squared Differences (SSD) method for obtaining a correlation between blocks of certain regions of the left and right images using light and shade information and summing squared differences, a Sum of Absolute Differences (SAD) method for obtaining a correlation between the blocks and summing absolute differences, and a normalized cross coefficient method using (or utilizing) correlation between pixels.
The local method can be performed well as the stereo matching when light and shade differences are clear.
However, since the local method uses the light and shade information only, it is difficult to precisely find similar images in a non-texture region, thereby causing false matching.
FIG. 1 is a view for explaining false matching in a non-texture region.
Referring to FIG. 1, a left image 10a and a right image 10b, each of which has a rectangular element 20a, 20b and a circular element 30a, 30b, are added to obtain a disparity map 10c using SAD as a disparity estimation method through a local method.
The left image 10a is composed of a first rectangular element 20a and a first circular element 30a in a non-texture region, and the right image 10b is composed of a second rectangular element 20b and a second circular element 30b in a non-texture region.
Here, the left image 10a is set as a reference image, and a certain block region is set around a reference pixel of the reference image. Then, the SAD disparity estimation method is performed to find a region in the right image most similar to the certain block region set around the left image using light and shade information.
While it is possible to find substantially similar regions in the non-texture regions of the left image 10a and the right image 10b, it does not provide the precise disparity.
As a result, the stereo matching using the local method generates distortion due to false matching of a third rectangular element 20c and a third circular element 30c in the non-texture region of the disparity map 10c. 